Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
Chen Change Loy, Timothy M. Hospedales, Tao Xiang,...
—SIFT-like local feature descriptors are ubiquitously employed in such computer vision applications as content-based retrieval, video analysis, copy detection, object recognition...
Christoph Strecha, Alexander A. Bronstein, Michael...
In this paper, we propose a bilevel sparse coding model for coupled feature spaces, where we aim to learn dictionaries for sparse modeling in both spaces while enforcing some desi...
We introduce two novel methods to improve the performance of wide area video surveillance applications by using scene features. First, we evaluate the drift in intrinsic and extri...
We recast the Cosegmentation problem using Random Walker (RW) segmentation as the core segmentation algorithm, rather than the traditional MRF approach adopted in the literature s...
Maxwell D. Collins, Jia Xu, Leo Grady, Vikas Singh